AIMC Topic: Electroencephalography

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Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes.

NeuroImage Sep 15, 2023
Electromagnetic source imaging (ESI) offers unique capability of imaging brain dynamics for studying brain functions and aiding the clinical management of brain disorders. Challenges exist in ESI due to the ill-posedness of the inverse problem and th...
Brain Deep Learning Magnetic Resonance Imaging Brain Mapping Humans Magnetoencephalography Drug Resistant Epilepsy Electrocorticography Electroencephalography Epilepsy
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Machine learning and EEG can classify passive viewing of discrete categories of visual stimuli but not the observation of pain.

BMC neuroscience Sep 15, 2023
Previous studies have demonstrated the potential of machine learning (ML) in classifying physical pain from non-pain states using electroencephalographic (EEG) data. However, the application of ML to EEG data to categorise the observation of pain ver...
Pain Humans Electroencephalography Random Forest Machine Learning
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Emotion recognition in EEG signals using deep learning methods: A review.

Computers in biology and medicine Sep 9, 2023
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making, planning, reasoning, and other mental states. As a result, they are considered a significant factor in human interactions. Human emotions can be identifie...
Deep Learning Emotions Electroencephalography Artificial Intelligence Reproducibility of Results Humans
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The Hybrid Deep Learning Model for Identification of Attention-Deficit/Hyperactivity Disorder Using EEG.

Clinical EEG and neuroscience Sep 8, 2023
Common misbehavior among children that prevents them from paying attention to tasks and interacting with their surroundings appropriately is attention-deficit/hyperactivity disorder (ADHD). Studies of children's behavior presently face a significant ...
Deep Learning Child Neural Networks, Computer Reproducibility of Results Electroencephalography Attention Deficit Disorder with Hyperactivity Humans
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Automatic identification of schizophrenia employing EEG records analyzed with deep learning algorithms.

Schizophrenia research Sep 8, 2023
Electroencephalography is a method of detecting and analyzing electrical activity in the brain. This electrical activity can be recorded and processed to aid in the clinical diagnosis of mental disorders. In this study, a novel system for classifying...
Electroencephalography Algorithms Support Vector Machine Deep Learning Signal Processing, Computer-Assisted Humans Bayes Theorem Schizophrenia
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A novel framework for classification of two-class motor imagery EEG signals using logistic regression classification algorithm.

PloS one Sep 8, 2023
Robotics and artificial intelligence have played a significant role in developing assistive technologies for people with motor disabilities. Brain-Computer Interface (BCI) is a communication system that allows humans to communicate with their environ...
Bayes Theorem Algorithms Humans Electroencephalography Logistic Models Artificial Intelligence
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3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 7, 2023
A novel multi-channel-based 3D convolutional neural network (3D-CNN) is proposed in this paper to classify sleep stages. Time domain features, frequency domain features, and time-frequency domain features are extracted from electroencephalography (EE...
Sleep Stages Electroencephalography Humans Electromyography Algorithms Deep Learning
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Deep learning for automated detection of generalized paroxysmal fast activity in Lennox-Gastaut syndrome.

Epilepsy & behavior : E&B Sep 6, 2023
OBJECTIVES: Generalized paroxysmal fast activity (GPFA) is a key electroencephalographic (EEG) feature of Lennox-Gastaut Syndrome (LGS). Automated analysis of scalp EEG has been successful in detecting more typical abnormalities. Automatic detection ...
Humans Brain Deep Learning Electroencephalography Lennox Gastaut Syndrome
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The influence of EEG channels and features significance on automatic detection of epileptic waves in MECT.

Computer methods in biomechanics and biomedical engineering Sep 5, 2023
Modified Electric Convulsive Therapy (MECT) is an efficacious physical therapy in treating mental disorders. The occurrence of epilepsy is a crucial benchmark for evaluating therapeutic effectiveness. However, the medical field still lacks relevant r...
Male Support Vector Machine Automation Epilepsy Humans Electroencephalography Signal Processing, Computer-Assisted Female
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ECG and EEG based detection and multilevel classification of stress using machine learning for specified genders: A preliminary study.

PloS one Sep 1, 2023
Mental health, especially stress, plays a crucial role in the quality of life. During different phases (luteal and follicular phases) of the menstrual cycle, women may exhibit different responses to stress from men. This, therefore, may have an impac...
Quality of Life Electrocardiography Female Male Humans Electroencephalography Machine Learning Corpus Luteum
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